A method for image compression with an associated arrangement is known from [1]. The known method serves in the MPEG (Motion Picture Expert Group) standard as a coding method and is substantially based on the hybrid DCT (Discrete Cosine Transform) with motion compensation. A similar method is used for video telephony using n×64 kbit/s (CCITT Recommendation H.261), for the TV contribution (CCR Recommendation 723) using 34 or 45 Mbits/s and for multimedia applications using 1.2 Mbit/s (ISO-MPEG-1). The hybrid DCT consists of a chronological processing stage that utilizes the kinship relations between successive images and a local processing stage that utilizes the correlation within an image.
The local processing (intraframe coding) basically corresponds to the conventional DCT coding. The image is broken down into blocks of 8×8 pixels that, in each case, are transformed to the frequency range via DCT. The result is a matrix of 8×8 coefficients that approximately reflects the two-dimensional local frequencies in the transformed image block. A coefficient with frequency 0 (direct component) represents a mean gray value of the image block.
Data expansion takes place after the transformation. Of course, a concentration of energy around the direct component (DC value) takes place in natural image masters, while the highest-frequency coefficients are mainly almost zero.
A spectral weighting of the coefficients takes place in the next stage, so that the amplitude accuracy of the high-frequency coefficients is reduced. This utilizes the properties of the human eye to resolve high local frequencies less accurately than low local frequencies.
A second stage in data reduction takes place in the form of an adaptive quantizing, via which the amplitude accuracy of the coefficient is further reduced or via which the small amplitudes are set to zero. The magnitude of the quantizing depends, in this case, on the occupancy of the output buffer. If the buffer is empty, a fine quantizing takes place and more data is generated. Conversely, the quantizing is coarser with a full buffer, which reduces the amount of data.
After the quantizing, the block is subject to zigzag scanning, which is followed by entropy coding, which further reduces the data. Two effects are used for this purpose.    1.) The statistics of the amplitude values (high amplitude values occur less frequently than small ones, so that long code words are allocated to the less-frequent events and short code words to the more-frequent events (variable-length coding (VLC)). In this way, a lower data rate is achieved on average than when coding using a fixed word length. The variable rate of the VLC is then smoothed in the buffer memory.    2.) The fact that in most cases only zeros follow from a specific value is utilized. Instead of all of these zeros, only an EOB (End Of Block) code is transmitted, which leads to a significant coding gain when compressing the image data. Instead of the initial rate of, for example, 512 bit, only 46 bit is then to be transmitted for this block, which corresponds to a compression factor of more than 11.
A further compression gain is obtained by chronological processing (interframe coding). To code differential images requires a lower data rate than for the original images, because the amplitude values are far lower.
Of course, the time differences are only small if the motions in the picture are also slight. If, on the other hand, the motions in the image are great, large differences occur which, in turn, are difficult to code. For this reason, the image-to-image motion is measured (motion estimation) and compensated for before forming the differential (motion compensation). In this case, the motion information is transmitted with the image information with only one motion vector per macroblock (e.g., four 8×8 image blocks) normally being used.
Yet further amplitude values of the differential images are obtained if a motion-compensated bidirectional prediction is utilized instead of the applied prediction.
In the case of a motion-compensated hybrid coder, the image signal itself is not transformed, but instead the chronological differential signal. For this reason, the coder also has a chronological recursive loop because the predictor must calculate the prediction value from the values of the already-transmitted (coded) images. An identical chronological recursive loop is located in the decoder so that the coder and decoder are fully synchronized.
In the MPEG-2 coding method there are mainly three different ways in which the images can be processed. These are as follows.    I-Images: No chronological prediction is used for the I-images; i.e., the image values are directly transformed and coded. I-images are used to be able to begin the decoding process again without knowledge of the past chronology, or to achieve a resynchronization during transmission errors.    P-Images: A chronological prediction is carried out using the P-images, with the DCT being applied to the chronological prediction error.    B-Images: With the B-images the chronological bidirectional prediction error is calculated and then transformed. The operation of the bidirectional prediction is basically adaptive; i.e., a forward prediction, a rearward prediction or an interpolation is permitted.
With the MPEG-2 coding, an image series is divided into so-called GOPs (Groups Of Pictures). n images from one I-image to the next form a GOP. The distance between the P-images is designated by m, with m−1 B-images being located, in each case, between the P-images. The MPEG syntax allows the user to decide how m and n are selected. m=1 means that no B-images are used and n=1 means that only I-images are coded.
A method for estimating motion as part of a method of block-based image coding is known from [2]. A precondition for this is that a digitized image has pixels that are assembled in image blocks of, in particular, 8×8 pixels or 16×16 pixels. If necessary, an image block also may include several image blocks. An example of this is a macroblock with six image blocks of which four image blocks are provided for luminosity information and two image block for color information.
Where there is a series of images, the following procedure is adopted for an image to be coded, taking account of the image blocks of this image.                A value for an error dimension is determined for the image block for which a motion estimation is to be made, in a chronologically preceding image starting from an image block that was in the same relative position in the preceding image (preceding image block). To do this, a total of the amounts of the differences between the coding information of the image block allocated to the pixels and of the preceding image block is preferably determined.        Coding information in this case is luminosity information (luminance value) and/or color information (chrominance value) which, in each case, is allocated to a pixel.        In a search area of presettable size and shape around the starting position in the chronologically preceding image, a value of the error dimension is determined, in each case, for an area of the same size as the preceding image block displaced by one or a half pixel.        In a search area of n×n pixels size n2 (error) values result. The particular displaced previous image block in the chronologically preceding image, for which the error dimension produces a minimum error value, is determined. For this image block, it is assumed that this previous image block coincides best with the image block of the image to be coded for which the motion estimation is to be made.        The result of the motion estimation is a motion vector with which the displacement between the image block in the image to be coded and the selected image block in the chronologically preceding image is described.        Compression of the image data is thus achieved in that the motion vector and the error signal are coded.        In particular, the motion estimation is performed for each image block of an image.        
An object-based image compression method is based on breaking down the image into objects with any type of margin. The individual objects are coded separate from each other in different video object plans, transmitted and again assembled in a receiver (decoder). As described above, with conventional coding methods the complete image is subdivided into square image blocks. This principle is also adopted in the object-based methods in that the object to be coded is broken down into square blocks and a separate motion estimation with motion compensation is separately performed for each block.
Where a series of images (image data) is transmitted through a disturbed communication channel, particularly a mobile (radio) channel or a wired loss-prone channel, parts of the image data can be lost. A loss of image data of this kind manifests itself in the form of severe reductions in quality in more or less large image areas. Because, as described above, with the image coding/image decoding method the motion estimation with motion compensation is used, the image interference does not disappear even if the transmission channel again guarantees error-free transmission. The reason for this is that, particularly once an error has occurred during the motion estimation, it persists up to transmission of the next full image (intra-image). Therefore, an extremely disturbing error propagation takes place.
Video data compression methods according to known standards (H.261, H.263, MPEG-1/2/4) use a motion-compensated prediction (motion estimation with error correction) and a transformation-based residual error coding with the discrete cosine transform being preferably used as the transformation coding. MPEG-2 contains suggestions for a scaleable coding (hierarchical coding). In this case, an image is subdivided into base information with a preset image quality and additional information that is additionally coded and transmitted to create a complete image quality (adequate image quality). Where there are transmission errors in the area of additional information, it is still ensured that the particular image can be reconstructed to a quality produced by the basic information.
An object of the present invention lies in providing of error-tolerant coding of a series of images, whereby the most efficient utilization possible of the disturbed channel can be achieved with regard to the image quality of the series of images.